Ultra-marathon events generally refer to any foot race involving distances longer than the classic marathon length of 42.195 km (Millet and Millet, 2012). During these events, the energy demand is likely to be at the extremes of human tolerance (Millet and Millet, 2012) and the knowledge of this aspect is still scarce (Hill and Davies, 2001; Ardigò and Capelli, 2012). This is likely due to the fact that to date there are no methods available to directly measure the energy demand over long periods of time without placing major (or minor) restrictions on the athletes' activity. However, the knowledge of the energy demand is important for ultra-marathons in general and, particularly, for extreme mountain ultra-marathon (MUM), where the ultra-long distance is coupled to run and/or walk on mountain trails with considerable positive and negative elevation changes and in a harsh mountainous environment (Vernillo et al., 2014, 2015). This information is essential to increase our understanding of the control of human locomotion resulting from the ability to appropriately regulate locomotor behavior in response to change in grade (Vernillo et al., 2016a).

Recently, a growing body of literature on the physiological and biomechanical changes associated with MUM has been published (for example, Millet et al., 2011; Morin et al., 2011; Saugy et al., 2013; Vernillo et al., 2014, 2015; Degache et al., 2015). For instance, our group (Vernillo et al., 2014) showed that after the world's most challenging MUM the energy cost of uphill running decreased by ~14%, due to changes in the uphill-running step mechanics that likely lead to a more economical running style. This improvement in the energy cost of uphill running has been confirmed by another study (Vernillo et al., 2016c). However, these studies investigated only pre-to-post changes. This aspect does not allow the understanding of the evolution of the energy demand during a MUM. Further, for this kind of competition most of the athletes tend to walk for longer sections of the race (Millet et al., 2011; Saugy et al., 2013; Vernillo et al., 2014; Degache et al., 2015). Thus, no physiological data set that provides insight on the influence of slope on the energy cost of walking measured during a MUM is available. Moreover, due to the difficulty to measure the energetics during the competitions (Vernillo et al., 2016c), research has been restricted to laboratory or non-mountainous outdoor settings. Thus, there are no data examining the effect of MUM in ecologically valid environments, thereby limiting our understanding on the physiological changes associated with MUM.

Accordingly, we report for the first time the case of an experienced MUM athlete who participated in the world's most challenging MUM (Saugy et al., 2013; Vernillo et al., 2014; Degache et al., 2015), with the aim to provide preliminary insights into the energy requirements as well as the physiological adaptations during the race.

There were 705 starters and 383 finishers (54.3%) in the 2013 race. The current record is 67 h 52 min 15 s (set in 2017 edition) and our participant completed the race in 125 h 12 min 19 s (139th place), sleeping for 11 h 40 min (9.3% of the total time). On average, the participant run/walked for 15 h and 40 min without sleeping (range, 2 to 23.5 h). Table 1 summarizes the changes in measurements retrieved during the six uphills. Length, gradient, altitude gain, s_vert and duration of each ascent, as well as sleeping behavior, are represented in Figure 1.

C and C_vert as a function of the gradient are presented in Figure 2. Participant's V˙O2peak and HR_peak were 48.1 mL·kg⁻¹·min⁻¹ and 169 beats·min⁻¹ respectively. Throughout the uphills, the mean exercise intensity was 57.3 ± 6.0% of V˙O2peak and 68.0 ± 8.7% of HR_peak. Further, mean C and C_vert were 11.4 ± 1.9 J·kg⁻¹·m⁻¹ and 57.9 ± 15.2 J·kg⁻¹·mvert−1, respectively (Table 1).

To the best of our knowledge, this is the first time that the energy cost of an official finisher of an extreme MUM has been described throughout the race. C and C_vert values are in line with the literature, being directly proportional to the slope in the range of gradients here investigated (Minetti et al., 2002; Giovanelli et al., 2015) (Figures 2A,B, respectively). Intuitively, one would assume that the greater distance performed during the MUM, coupled with a fatigue state, should be associated with a drift upwards of the exercise intensity and a rise in the energy cost. However, an intriguing finding of the present study was that the mean exercise intensity, expressed as %V˙O2peak and %HR_peak, was similar during the six uphill sections (Table 1). Further, C, C_vert, as well as Eff_mech, did not increase throughout the MUM, with the lowest values occurred in the first but also in the last two uphills (Table 1).

Though it can be questionable to generalize the results obtained by investigating a single participant, we can speculate that the improvements found at day 5 and 6 (Figure 2) likely originated from a generic improvement in the mechanical efficiency of locomotion, as already observed in a group of women after a trekking expedition (Tam et al., 2016). Further, this generic improvement in the mechanical efficiency of locomotion could also be responsible for the decreased (improvement) in the uphill energy cost that our group already observed at the end of the same MUM (Vernillo et al., 2014, 2016c). Throughout the MUM, the participant walked during the uphill sections, while adopted a “smoother” running technique during both the flat and downhill sections (authors' personal communication). This strategy likely had the aim to attenuate the overall load faced by his locomotor system at each step (Morin et al., 2011; Millet et al., 2012; Degache et al., 2015). Since uphill locomotion has a movement specific pattern (Vernillo et al., 2016a), this prolonged and repetitive technique likely reflected positive adaptations in the participant's energy requirements and physiological variables during the ~75 h of uphill activity.

We presented the case of a 50-years-old ultra-marathon athlete with the aim to provide insights into the energy requirements as well as the physiological adaptations during an extreme MUM race. Despite this is a case study and, thus, the generalizability of our findings to all the MUM participants should be done with caution, the present report could be considered a step forward in the analysis of this kind of topic considering the difficulty to apply these measures on the field (Vernillo et al., 2016c). The results indicate that, despite the distance performed during the MUM (i.e., 330 km with +24,000 m D+) the participant did not experience a metabolic fatigue state perhaps due to the prolonged and repetitive locomotion gesture, thereby reflecting a generic improvement in the mechanical efficiency of locomotion (Tam et al., 2016; Vernillo et al., 2016c). These data likely suggest that incorporating long-lasting uphill locomotion training, and hence predisposition to sustaining such loading, is mandatory in the training programs of mountain ultra-marathon athletes to optimize the training process governing this performance.

Conceived and designed the experiments: AS, PT, FD, GM, GV and FS. Performed experiments: AS, PT, EL, FD. Analyzed data: AS, AF, GM and GV. Interpreted results of research: AS, AF, PT, EL, AL, GM, GV and FS. Drafted manuscript and prepared tables/figures: AS, AF, EL, BP, GV and FS. Edited, critically revised paper and approved final version of manuscript: AS, AF, PT, EL, AL, FD, BP, GM, GV and FS. All authors have agreed to be accountable for all aspects of the work related to its accuracy and integrity.